Workflow Templates

9 nodes480 views

Turns Reddit Pain Points into Comic Ads using Dumpling AI and GPT-4o

by Yang

📝 Description 🤖 What this workflow does This workflow turns Reddit pain points into emotionally-driven comic-style ads using AI. It takes in a product description, scrapes Reddit for real user pain points, filters relevant posts using AI, generates ad angles, rewrites them into 4-panel comic prompts, and finally uses Dumpling AI to generate comic-style images. All final creatives are uploaded to Google Drive. 🧠 What problem is this solving? Crafting ad content that truly speaks to customer struggles is time-consuming. This workflow automates that entire process — from pain point discovery to visual creative output — using AI and Reddit as a source of truth for customer language. 👤 Who is this for? Copywriters and performance marketers Startup founders and indie hackers Creatives building empathy-driven ad concepts Automation experts looking to generate scroll-stopping content ⚙️ Setup Instructions Here’s how to set everything up, step by step: 🔹 1. Trigger: Form Input Node: 📝 Form - Submit Product Info This form asks the user to enter: Brand Name Website Product Description ✅ Make sure this form is active and testable. 🔹 2. Generate Reddit Keyword Node: 🧠 GPT-4o - Generate Reddit Keyword Uses the product description to generate a search keyword based on what your audience might be discussing on Reddit. 🔹 3. Search Reddit Node: 🔍 Reddit - Search Posts Uses the keyword to search Reddit for relevant threads. Make sure your Reddit integration is properly configured. 🔹 4. Filter Valid Posts Node: 🔎 IF - Check Upvotes & Text Length Filters out low-effort or unpopular posts. Only keeps posts with: Minimum 2 upvotes Content at least 100 characters long ✅ You can adjust these thresholds in the node settings. 🔹 5. Clean Reddit Output Node: 🧼 Code - Structure Reddit Posts This formats the list of posts into clean JSON for the AI agents to process. 🔹 6. Check Relevance with AI Agent Node: 🤔 Langchain Agent - Post Relevance Classifier This node uses a LangChain agent (tool: think2) to determine if each post is relevant to your product. Only relevant ones are passed forward. 🔹 7. Aggregate Relevant Posts Node: 📦 Code - Merge Relevant Posts Collects all relevant posts into a clean format for the next GPT-4 call. 🔹 8. Generate Ad Angles Node: ✍️ GPT-4o - Generate Emotional Ad Angles Writes 10 pain-point-based marketing angles using real customer language. 🔹 9. Rank the Best Angles Node: 📊 GPT-4o - Rank Top 10 Angles Scores the generated angles and ranks them from most to least powerful. Only the top 3 are passed forward. 🔹 10. Turn Angles into Comic Prompts Node: 🎭 GPT-4o - Write Comic Scene Prompts Rewrites each of the top ad angles into a 4-panel comic strip structure (pain → tension → product → resolution). 🔹 11. Generate Comic Images Node: 🎨 Dumpling AI - Generate Comic Panels Sends each prompt to Dumpling AI to create visual comic scenes. 🔹 12. Wait for Image Generation Node: ⏳ Wait - Dumpling AI Response Time Adds a delay to give Dumpling AI time to finish generating all images. 🔹 13. Get Final Image URLs Node: 🔗 Code - Extract Image URLs from Dumpling Response Extracts all image links for preview/download. 🔹 14. Upload to Google Drive Node: ☁️ Google Drive - Upload Comics Uploads the comic images to your chosen Google Drive folder. ✅ Update this node with your destination folder ID. 🔹 15. Log Final Output Optional You can extend the flow to log the image links, ad angles, and Reddit sources to Google Sheets, Airtable, or Notion depending on your use case. 🛠️ How to Customize ✏️ Adjust tone: Update GPT-4 system prompts to sound more humorous, emotional, or brand-specific. 🧵 Use different styles: Swap Dumpling AI image settings for ink sketch, manga, or cartoon renderings. 🔄 Change input source: Replace Reddit with X (Twitter), Quora, or YouTube comments. 📦 Store results differently: Swap Google Drive for Notion, Dropbox, or Airtable. This workflow turns real audience struggles into thumb-stopping comic content — automatically.

🤖AI & Machine Learning

8 nodes145 views

Gmail MCP Workflow - AI-Powered Email Management

by David Olusola

💬Communication & Collaboration

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. MCP Gmail Workflow – AI-Powered Email Management ✨ What It Does A smart n8n workflow that connects Gmail with an AI agent (via MCP), letting you send, read, and organize emails using natural language. ⚙️ Key Features 🧠 AI Commands: “Send email to John about the budget” 📥 Inbox Control: Mark read/unread, apply/remove labels 🗂 Smart Organization: Auto-label based on content 🤖 MCP-Ready: Works with Claude, ChatGPT, etc. 🎯 Use Cases “📤 Send a follow-up to the client about yesterday’s meeting” “📬 Mark all newsletters as read and label ‘Newsletter’” “🧾 Summarize latest email from Sarah” “🗃 Label all Project X emails as ‘Project-X-2024’” “⭐ Find unread emails from my manager and mark as important” 🛠 Setup Guide 🔑 Prerequisites n8n (self-hosted or cloud) Gmail API credentials MCP-compatible AI (optional but powerful) 📥 1. Import Workflow Copy JSON → Open n8n → Import → Paste → Done ✅ 🔐 2. Gmail OAuth2 Setup Create Google project → Enable Gmail API Create OAuth2 creds → Add n8n redirect URI In n8n: Add Gmail OAuth2 → Paste Client ID/Secret → Connect 🧩 3. Update Credential References Find your credential ID in n8n Update each Gmail node with your ID 🧠 4. MCP Trigger (Optional) Use provided webhook URL in your AI system Send test prompts to verify connection 🧪 5. Test Key Actions ✅ “Send a test email” ✅ “Read latest email” ✅ “Label last email as ‘Test’” ✅ “Mark latest email as unread” ⚙️ 6. Advanced Tips Create custom labels in Gmail Use HTTPS + webhook auth Add retries and error handling in n8n 🧯 Troubleshooting ❗ Gmail Auth Error? → Re-auth and check redirect URI ❗ Webhook not firing? → Check endpoint + manual test ❗ Label errors? → Use correct label names or IDs ✅ Required Gmail Scopes: gmail.modify gmail.send 📈 Best Practices 🔁 Test regularly 🔒 Use minimal permissions 🏷 Consistent label naming 🔍 Monitor execution + webhook logs 🎉 You’re All Set! Control Gmail with your voice or text through AI. Make managing emails smarter, faster, and 100% automated 💌

beginner

0 nodes124 views

AI-Powered Telegram Trivia Bot with Auto Question Generation & User Management

by Luka Zivkovic

Complete Telegram Trivia Bot with AI Question Generation Build a fully-featured Telegram trivia bot that automatically generates fresh questions daily using OpenAI and tracks user progress with NocoDB. Perfect for communities, education, or entertainment! ✨ Key Features 🤖 AI Question Generation: Automatically creates 40+ new trivia questions daily across 8 categories 📊 Smart User Management: Tracks scores, prevents question repeats, maintains leaderboards 🎮 Game Mechanics: Star-based difficulty scoring, answer history, progress tracking 🏆 Competitive Elements: Real-time leaderboards with emoji rankings and user positioning 🛡️ Robust Architecture: Error handling, state management, and data validation 🚀 Perfect For Community Engagement**: Keep Telegram groups active with daily trivia challenges Educational Content**: Create learning experiences with categorized questions Business Applications**: Employee training, customer engagement, lead generation Personal Projects**: Learn n8n automation while building something fun 📱 Supported Commands /start - Welcome new users with setup instructions /question - Get personalized trivia questions (never repeats correctly answered ones) /score - View current points and statistics /leaderboard - See top 10 players with rankings /stats - Detailed accuracy and performance metrics /help - Complete command reference 🔧 How It Works User Journey: User sends /question command to bot System checks their answer history to avoid repeats Displays fresh question with multiple choice options Processes answer, updates score based on difficulty stars Saves complete answer history for future filtering AI Content Pipeline: Daily scheduler triggers question generation OpenAI creates 5 questions per category (8 categories total) Questions automatically saved to NocoDB with difficulty ratings Content includes explanations and proper formatting 🛠️ Set Up Steps Prerequisites: n8n instance (cloud or self-hosted) NocoDB database (free tier works) OpenAI API key (Not required if you want to add questions yourself) Telegram bot token Database Setup: Create 3 NocoDB tables with the exact field specifications provided in the sticky notes. The workflow includes complete schema documentation. Configuration Time: ~15 minutes for database setup + API keys Detailed Setup Instructions: All setup steps, database schemas, and configuration details are documented in the workflow's sticky notes for easy implementation. 📈 Advanced Features Question History Tracking**: Users never see correctly answered questions again Difficulty-Based Scoring**: 1-5 star rating system with corresponding points Category Management**: 8 different trivia categories for variety State Management**: Proper game flow with idle/waiting states Error Handling**: Graceful fallbacks for all edge cases Scalable Architecture**: Supports unlimited concurrent users 🎯 Business Applications Lead Generation**: Capture user data through engaging trivia Employee Training**: Create custom questions for onboarding Customer Engagement**: Keep users active in your Telegram community Educational Tools**: Subject-specific learning with progress tracking Event Activation**: Conferences, workshops, or team building 💡 Customization Options Modify question categories for your niche Adjust scoring systems and difficulty levels Add custom commands and features Integrate with other platforms or APIs Create specialized question sets 🔗 Get Started Ready to build your own AI-powered trivia bot? Start with n8n and follow the comprehensive setup guide included in this workflow template. Next Steps: Import this workflow template Follow the database setup instructions in sticky notes Configure your API credentials Test with sample questions Launch your trivia bot! Turn your friend group into trivia champions with AI-generated questions that spark friendly competition!

⚙️Business Automation

4 nodes349 views

⚡📽️ Ultimate AI-Powered Chatbot for YouTube Summarization & Analysis

by Joseph LePage

🎥 YouTube Video AI Agent Workflow This n8n workflow template allows you to interact with an AI agent that extracts details and the transcript of a YouTube video using a provided video ID. Once the details and transcript are retrieved, you can chat with the AI agent to explore or analyze the video's content in a conversational and insightful manner. 🌟 How the Workflow Works 🔗 Input Video ID: The user provides a YouTube video ID as input to the workflow. 📄 Data Retrieval: The workflow fetches essential details about the video (e.g., title, description, upload date) and retrieves its transcript using YouTube's Data API and additional tools for transcript extraction. 🤖 AI Agent Interaction: The extracted details and transcript are processed by an AI-powered agent. Users can then ask questions or engage in a conversation with the agent about the video's content, such as: Summarizing the transcript. Analyzing key points. Clarifying specific sections. 💬 Dynamic Responses: The AI agent uses natural language processing (NLP) to generate contextual and accurate responses based on the video data, ensuring a smooth and intuitive interaction. 🚀 Use Cases 📊 Content Analysis**: Quickly analyze long YouTube videos by querying specific sections or extracting summaries. 📚 Research and Learning**: Gain insights from educational videos or tutorials without watching them entirely. ✍️ Content Creation**: Repurpose transcripts into blogs, social media posts, or other formats efficiently. ♿ Accessibility**: Provide an alternative, text-based way to interact with video content for users who prefer reading over watching. 🛠️ Resources for Getting Started Google Cloud Console** (for API setup): Visit Google Cloud's Get Started Guide to configure your API access. YouTube Data API Key Setup**: Follow this guide to create and manage your YouTube Data API key. Install n8n Locally**: Refer to this installation guide for setting up n8n on your local machine. ✨ Sample Prompts "Tell me about this YouTube video with id: JWfNLF_g_V0" "Can you provide a list of key takeaways from this video with id: [youtube-video-id]?"

🤖AI & Machine Learning

6 nodes17636 views

AWS Cost & Usage Report Management for AI Agents

by David Ashby

Complete MCP server exposing 4 AWS Cost and Usage Report Service API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add AWS Cost and Usage Report Service credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the AWS Cost and Usage Report Service API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to http://cur.{region}.amazonaws.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (4 total) 🔧 #X-Amz-Target=Awsorigamiservicegatewayservice.Deletereportdefinition (1 endpoints) • POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.DeleteReportDefinition: Deletes the specified report. 🔧 #X-Amz-Target=Awsorigamiservicegatewayservice.Describereportdefinitions (1 endpoints) • POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.DescribeReportDefinitions: Lists the AWS Cost and Usage reports available to this account. 🔧 #X-Amz-Target=Awsorigamiservicegatewayservice.Modifyreportdefinition (1 endpoints) • POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.ModifyReportDefinition: Allows you to programatically update your report preferences. 🔧 #X-Amz-Target=Awsorigamiservicegatewayservice.Putreportdefinition (1 endpoints) • POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.PutReportDefinition: Creates a new report using the description that you provide. 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native AWS Cost and Usage Report Service API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Create a WHOIS API Interface for AI Agents with 8 Domain Management Operations

by David Ashby

Complete MCP server exposing 8 Bulk WHOIS API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Bulk WHOIS API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Bulk WHOIS API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to http://localhost:5000 • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (8 total) 🔧 Batch (4 endpoints) • GET /batch: Get your batches • POST /batch: Create batch. Batch is then being processed until all provided items have been completed. At any time it can be get to provide current status with results optionally. • DELETE /batch/{id}: Delete batch • GET /batch/{id}: Get batch 🔧 Db (1 endpoints) • GET /db: Query domain database 🔧 Domains (3 endpoints) • GET /domains/{domain}/check: Check domain availability • GET /domains/{domain}/rank: Check domain rank (authority). • GET /domains/{domain}/whois: WHOIS query for a domain 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Bulk WHOIS API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

File Hash Verification for AI Agents with hashlookup CIRCL API

by David Ashby

Complete MCP server exposing 11 hashlookup CIRCL API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add hashlookup CIRCL API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the hashlookup CIRCL API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://hashlookup.circl.lu • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (11 total) 🔧 Bulk (2 endpoints) • POST /bulk/md5: Bulk Search MD5 Hashes • POST /bulk/sha1: Bulk Search SHA1 Hashes 🔧 Children (1 endpoints) • GET /children/{sha1}/{count}/{cursor}: Return children from a given SHA1. A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0. 🔧 Info (1 endpoints) • GET /info: Get Database Info 🔧 Lookup (3 endpoints) • GET /lookup/md5/{md5}: Lookup MD5. • GET /lookup/sha1/{sha1}: Lookup SHA-1. • GET /lookup/sha256/{sha256}: Lookup SHA-256. 🔧 Parents (1 endpoints) • GET /parents/{sha1}/{count}/{cursor}: Return parents from a given SHA1. A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0. 🔧 Session (2 endpoints) • GET /session/create/{name}: Create a session key to keep search context. The session is attached to a name. After the session is created, the header hashlookup_session can be set to the session name. • GET /session/get/{name}: Return set of matching and non-matching hashes from a session. 🔧 Stats (1 endpoints) • GET /stats/top: Get Top Queries 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native hashlookup CIRCL API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Convert YouTube Videos to Shorts with Klap & Auto-Post to Multiple Social Platforms

by Dr. Firas

💬Communication & Collaboration

Convert YouTube videos to viral Shorts with Klap and auto-post with Blotato > ⚠️ Disclaimer: This workflow uses Community Nodes and requires a self-hosted n8n instance. Who is this for? This workflow is perfect for content creators, YouTubers, marketing teams and entrepreneurs who want to effortlessly convert long YouTube videos into short, viral-ready clips and publish them automatically on TikTok, Instagram, YouTube Shorts and other platforms. What problem is this workflow solving? Manually creating short, engaging clips from YouTube videos takes hours: Selecting highlights Adding subtitles and effects Downloading and editing Posting individually on each platform This workflow eliminates all of that: AI-powered Shorts generation with Klap Smart scheduling based on your posting calendar Full automation of uploads to multiple platforms What this workflow does From a simple YouTube link sent via Telegram, the workflow: Extracts the YouTube URL and number of Shorts requested Sends the video to Klap for AI-powered Shorts generation Checks when the Shorts are ready Schedules publication times based on your custom settings Uploads the Shorts to Blotato Auto-posts on TikTok, YouTube Shorts, Instagram and more Sends a confirmation recap to Telegram Setup Connect your Telegram bot to the trigger node Add your Klap API key for video processing Link your Google Sheets with your scheduling preferences Add your Blotato API key and social platform IDs Adjust the number of Shorts generated if needed Modify the scheduling logic or time windows in the Google Sheets How to customize this workflow to your needs Change AI video settings in the Klap API request Adjust time windows and frequency in the scheduling nodes Limit the workflow to specific platforms (e.g., TikTok only) Add a manual approval step before publishing Modify the Telegram recap message content 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube

4 nodes1600 views

Transportation Laws and Incentives MCP Server

by David Ashby

Complete MCP server exposing 4 Transportation Laws and Incentives API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Transportation Laws and Incentives credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Transportation Laws and Incentives API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to http://developer.nrel.gov/api/transportation-incentives-laws • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (4 total) 🔧 V1.{Output_Format} (1 endpoints) • GET /v1.{output_format}: Return a full list of laws and incentives that match your query. 🔧 V1 (3 endpoints) • GET /v1/category-list.{output_format}: Return the law categories for a given category type. • GET /v1/pocs.{output_format}: Get the points of contact for a given jurisdiction. • GET /v1/{id}.{output_format}: Fetch the details of a specific law given the law's ID. 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Transportation Laws and Incentives API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Create and Manage Short URLs with Telegram Bot, MongoDB and Nginx Redirects

by Rudi Afandi

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow allows you to create and manage custom short URLs directly via Telegram, with all data stored in MongoDB, and redirects handled efficiently via Nginx. How it works This flow provides a seamless URL shortening experience: Create via Telegram: Send a long URL to your bot. It will ask if you want a custom short code. Store in MongoDB: All long URLs and their corresponding short codes are securely stored in your MongoDB instance. Fast Redirects: When a user accesses a short URL, Nginx forwards the request to a dedicated n8n webhook, which then quickly redirects them to the original long URL. Set up steps This setup is straightforward, especially if you already have a running n8n instance and a VPS. Difficulty: Medium (Basic n8n/VPS knowledge required) Estimated Time: 15-30 minutes n8n Instance & VPS: Ensure you have n8n running on your VPS (e.g., 2 core 2GB, as you have). Telegram Bot: Create a new bot via @BotFather and get your Bot Token. Add this as a Telegram credential in n8n. MongoDB Database: Set up a MongoDB instance (either on your VPS or a cloud service like MongoDB Atlas). Create a database and a collection (e.g., url or short_urls). Add your MongoDB credentials in n8n. Here's MongoDB data structure JSON: >[ {"_id": "686a11946a48b580d72d0397", "longUrl": "https://longurl.com/abcdefghijklm/", "shortUrl": "short-code"} ] Domain/Subdomain: Point a domain or subdomain (e.g., s.yourdomain.com) to your VPS IP address. This will be your short URL base. Nginx/Caddy Configuration: Configure your web server (Nginx or Caddy) on the VPS to proxy requests from your short URL domain to the n8n webhook for redirects. (Detailed Nginx config is provided as sticky notes in the redirect workflow) Workflow Setup: Import both provided n8n workflows (Telegram URL Shortener Creator and URL Redirect Handler). Activate both workflows. Crucial: Set an environment variable in your n8n instance (or .env file) named SHORTENER_DOMAIN with the value of your short URL domain (e.g., https://s.yourdomain.com). Refer to sticky notes inside the workflows for detailed node configurations and expressions.

Automate Vendor Due Diligence Research with Gemini & Jina AI

by Adnan